Cost-Effectiveness and Efficacy of spa, SCCmec, and PVL Genotyping of Methicillin-Resistant Staphylococcus aureus as Compared to Pulsed-Field Gel Electrophoresis
Bibliographic record
Abstract
Pulsed-field gel electrophoresis (PFGE) is a valuable molecular typing assay used for methicillin-resistant Staphylococcus aureus (MRSA) surveillance and genotyping. However, there are several limitations associated with PFGE. In Alberta, Canada, the significant increase in the number of MRSA isolates submitted to the Provincial Laboratory for Public Health (ProvLab) for PFGE typing led to the need for an alternative genotyping method. In this study, we describe the transition from PFGE to Staphylococcus protein A (spa), Staphylococcal cassette chromosome (SCCmec), and Panton-Valentine leukocidin (PVL) typing. A total of 1915 clinical MRSA isolates collected from 2005 to 2009 were used to develop and validate an algorithm for assigning PFGE epidemic types using spa, SCCmec, and PVL typing and the resulting data was used to populate a new Alberta MRSA typing database. An additional 12620 clinical MRSA isolates collected from 2010 to 2012 as part of ongoing routine molecular testing at ProvLab were characterized using the new typing algorithm and the Alberta MRSA typing database. Switching to spa, SCCmec, and PVL from PFGE typing substantially reduced hands-on and turn-around times while maintaining historical PFGE epidemic type designations. This led to an approximate $77,000 reduction in costs from 2010 to 2012. PFGE typing is still required for a small subset of MRSA isolates that have spa types that are rare, novel, or associated with more than one PFGE epidemic type.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".